REINFORCE — REINFORCE Algorithm

Fact

An RL method that updates a policy using the reward after a full try.

In Plain Words

REINFORCE is like a coach watching one full basketball play. If the shot goes in, the whole play gets a gold star.

It improves the AI's policy, or habit for choosing moves. It fits tasks scored after the round ends.

Related Concepts

• Policy Gradient
• Reinforcement Learning
• Actor-Critic
• Reinforcement Learning from Human Feedback

Policy Gradient
REINFORCE is a classic starter form of Policy Gradient.

RL
It uses rewards from the environment to update the policy directly.

Actor-Critic
Actor-Critic improves on REINFORCE and makes learning less noisy.

RLHF
RLHF keeps this RL idea when it optimizes a model's policy.